We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
An ideal shape model should be both invariant to global transformations and robust to local distortions. In this paper we present a new shape modeling framework that achieves both...
This paper addresses the need for designing user interfaces (UIs) to workflow information systems by adopting a model-centric approach. We introduce a conceptual workflow model to...
—The use of multiple entropy models for Huffman or arithmetic coding is widely used to improve the compression efficiency of many algorithms when the source probability distribu...
In this paper, we describe a method of shape-based 3D model retrieval that employs a set of 3D, local, multi-scale features extracted from a voxel representation of a 3D model to ...